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Record W2892369420 · doi:10.5038/1911-9933.11.3.1548

Book Review: Reichsrock: The International Web of White-Power and Neo-Nazi Hate Music

2018· article· en· W2892369420 on OpenAlexvenueno aff
Christiane Alsop

Bibliographic record

VenueGenocide Studies and Prevention · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicItalian Fascism and Post-war Society
Canadian institutionsnot available
Fundersnot available
KeywordsNazismGenocidePower (physics)White (mutation)Political scienceMedia studiesArtSociologyLawPoliticsBiology

Abstract

fetched live from OpenAlex

In mid-July 2017, six thousand people gathered at the white-power music festival Rock gegen Überfremdung (Rock against Foreign Domination) in Themar, a small town in Thuringia, Germany.At the event, the police recorded forty-six crimes, including assault, threatening behavior, contravention of German weapons law and displaying illegal (i.e.Nazi) symbols.Six people were arrested and the authorities recorded the identities of 440 festival-goers.An undisclosed sum was raised for the far-right political cause. 1 Music festivals of this kind and the violence that accompanies them are part of today's German political reality and, increasingly, of other countries around the world.This makes the white-power music scene worth the attention of any scholar studying extremist political movements, racism, or genocide.The ethnomusicologist and genocide historian Kirsten Dyck is one of them.Unlike other scholars in the field of white-power music, she looks beyond the country-specific variations of such music scenes, and, in her book Reichsrock, makes a convincing case that festivals like the one in Thuringia are anything but fringe phenomena.On the contrary, as she reveals, the white-power music scene has become a diffuse ideological network with interconnected outposts in countries around the world.Dyck begins by explaining why she applies the term white-power-as opposed to whitesupremacist or white-nationalist-to the music scene she investigates.Because its promoters are convinced that the existence of the white race is threatened, their music must express a sense of power and of their empowerment.The umbrella term white-power music encompasses many local scenes, each with its own type of pro-white racist music; its musicians and fans may or may not interact or agree with their counterparts in other regions.She defines white-power music as "any music produced and distributed by individuals who are actively trying to advance what they view as a white-power or pro-white racist agenda." 2 In general, these individuals believe in a so-called international Jewish conspiracy and stand in opposition to national governments and international power structures like the United Nations or the World Bank while displaying hostility toward racial, ethnic and sexual minorities.3 White-power music allows the far right to generate money for its cause, to disseminate its ideology, to offer opportunities for social bonding, and to provide a way in to white-power beliefs and activism for those who haven't yet had interest in or contact with such ideological beliefs and communities.Dyck sets two ambitious goals for herself.The first is to present an in-depth study of whitepower music as a transnational rather than merely a local phenomenon; the second is to explore the connections between seemingly non-racist elements of mainstream ideology and the blatantly racist aspects of white-power philosophy.Although issues of gender and religion are central themes of white-power ideology and music, they remain excluded from this study; the author plans to focus on them in her future work.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.006
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0260.013

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.314
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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